Articles | Volume 17, issue 6
https://doi.org/10.5194/tc-17-2487-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-17-2487-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
23 Jun 2023
Research article |
| 23 Jun 2023
| 23 Jun 2023
A decade-plus of Antarctic sea ice thickness and volume estimates from CryoSat-2 using a physical model and waveform fitting
Steven Fons
Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA
Cryospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA
Nathan Kurtz
CORRESPONDING AUTHOR
Cryospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA
Marco Bagnardi
Cryospheric Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, MD, USA
ADNET Systems, Inc., Bethesda, MD, USA
Related authors
Robert Ricker, Steven Fons, Arttu Jutila, Nils Hutter, Kyle Duncan, Sinead L. Farrell, Nathan T. Kurtz, and Renée Mie Fredensborg Hansen
The Cryosphere, 17, 1411–1429, https://doi.org/10.5194/tc-17-1411-2023, https://doi.org/10.5194/tc-17-1411-2023, 2023
Short summary
Short summary
Information on sea ice surface topography is important for studies of sea ice as well as for ship navigation through ice. The ICESat-2 satellite senses the sea ice surface with six laser beams. To examine the accuracy of these measurements, we carried out a temporally coincident helicopter flight along the same ground track as the satellite and measured the sea ice surface topography with a laser scanner. This showed that ICESat-2 can see even bumps of only few meters in the sea ice cover.
Steven W. Fons and Nathan T. Kurtz
The Cryosphere, 13, 861–878, https://doi.org/10.5194/tc-13-861-2019, https://doi.org/10.5194/tc-13-861-2019, 2019
Short summary
Short summary
A method to measure the snow freeboard of Antarctic sea ice from CryoSat-2 data is developed. Through comparisons with data from airborne campaigns and another satellite mission, we find that this method can reasonably retrieve snow freeboard across the Antarctic and shows promise in retrieving snow depth in certain locations. Snow freeboard data from CryoSat-2 are important because they enable the calculation of sea ice thickness and help to better understand snow depth on Antarctic sea ice.
Michael Studinger, Benjamin E. Smith, Nathan Kurtz, Alek Petty, Tyler Sutterley, and Rachel Tilling
The Cryosphere, 18, 2625–2652, https://doi.org/10.5194/tc-18-2625-2024, https://doi.org/10.5194/tc-18-2625-2024, 2024
Short summary
Short summary
We use green lidar data and natural-color imagery over sea ice to quantify elevation biases potentially impacting estimates of change in ice thickness of the polar regions. We complement our analysis using a model of scattering of light in snow and ice that predicts the shape of lidar waveforms reflecting from snow and ice surfaces based on the shape of the transmitted pulse. We find that biased elevations exist in airborne and spaceborne data products from green lidars.
Robert Ricker, Steven Fons, Arttu Jutila, Nils Hutter, Kyle Duncan, Sinead L. Farrell, Nathan T. Kurtz, and Renée Mie Fredensborg Hansen
The Cryosphere, 17, 1411–1429, https://doi.org/10.5194/tc-17-1411-2023, https://doi.org/10.5194/tc-17-1411-2023, 2023
Short summary
Short summary
Information on sea ice surface topography is important for studies of sea ice as well as for ship navigation through ice. The ICESat-2 satellite senses the sea ice surface with six laser beams. To examine the accuracy of these measurements, we carried out a temporally coincident helicopter flight along the same ground track as the satellite and measured the sea ice surface topography with a laser scanner. This showed that ICESat-2 can see even bumps of only few meters in the sea ice cover.
Alek A. Petty, Nicole Keeney, Alex Cabaj, Paul Kushner, and Marco Bagnardi
The Cryosphere, 17, 127–156, https://doi.org/10.5194/tc-17-127-2023, https://doi.org/10.5194/tc-17-127-2023, 2023
Short summary
Short summary
We present upgrades to winter Arctic sea ice thickness estimates from NASA's ICESat-2. Our new thickness results show better agreement with independent data from ESA's CryoSat-2 compared to our first data release, as well as new, very strong comparisons with data collected by moorings in the Beaufort Sea. We analyse three winters of thickness data across the Arctic, including 50 cm thinning of the multiyear ice over this 3-year period.
Isolde A. Glissenaar, Jack C. Landy, Alek A. Petty, Nathan T. Kurtz, and Julienne C. Stroeve
The Cryosphere, 15, 4909–4927, https://doi.org/10.5194/tc-15-4909-2021, https://doi.org/10.5194/tc-15-4909-2021, 2021
Short summary
Short summary
Scientists can estimate sea ice thickness using satellites that measure surface height. To determine the sea ice thickness, we also need to know the snow depth and density. This paper shows that the chosen snow depth product has a considerable impact on the findings of sea ice thickness state and trends in Baffin Bay, showing mean thinning with some snow depth products and mean thickening with others. This shows that it is important to better understand and monitor snow depth on sea ice.
Ron Kwok, Alek A. Petty, Marco Bagnardi, Nathan T. Kurtz, Glenn F. Cunningham, Alvaro Ivanoff, and Sahra Kacimi
The Cryosphere, 15, 821–833, https://doi.org/10.5194/tc-15-821-2021, https://doi.org/10.5194/tc-15-821-2021, 2021
Michael Studinger, Brooke C. Medley, Kelly M. Brunt, Kimberly A. Casey, Nathan T. Kurtz, Serdar S. Manizade, Thomas A. Neumann, and Thomas B. Overly
The Cryosphere, 14, 3287–3308, https://doi.org/10.5194/tc-14-3287-2020, https://doi.org/10.5194/tc-14-3287-2020, 2020
Short summary
Short summary
We use repeat airborne geophysical data consisting of laser altimetry, snow, and Ku-band radar and optical imagery to analyze the spatial and temporal variability in surface roughness, slope, wind deposition, and snow accumulation at 88° S. We find small–scale variability in snow accumulation based on the snow radar subsurface layering, indicating areas of strong wind redistribution are prevalent at 88° S. There is no slope–independent relationship between surface roughness and accumulation.
Dyre O. Dammann, Leif E. B. Eriksson, Son V. Nghiem, Erin C. Pettit, Nathan T. Kurtz, John G. Sonntag, Thomas E. Busche, Franz J. Meyer, and Andrew R. Mahoney
The Cryosphere, 13, 1861–1875, https://doi.org/10.5194/tc-13-1861-2019, https://doi.org/10.5194/tc-13-1861-2019, 2019
Short summary
Short summary
We validate TanDEM-X interferometry as a tool for deriving iceberg subaerial morphology using Operation IceBridge data. This approach enables a volumetric classification of icebergs, according to volume relevant to iceberg drift and decay, freshwater contribution, and potential impact on structures. We find iceberg volumes to generally match within 7 %. These results suggest that TanDEM-X could pave the way for future interferometric systems of scientific and operational iceberg classification.
Steven W. Fons and Nathan T. Kurtz
The Cryosphere, 13, 861–878, https://doi.org/10.5194/tc-13-861-2019, https://doi.org/10.5194/tc-13-861-2019, 2019
Short summary
Short summary
A method to measure the snow freeboard of Antarctic sea ice from CryoSat-2 data is developed. Through comparisons with data from airborne campaigns and another satellite mission, we find that this method can reasonably retrieve snow freeboard across the Antarctic and shows promise in retrieving snow depth in certain locations. Snow freeboard data from CryoSat-2 are important because they enable the calculation of sea ice thickness and help to better understand snow depth on Antarctic sea ice.
Ron Kwok, Nathan T. Kurtz, Ludovic Brucker, Alvaro Ivanoff, Thomas Newman, Sinead L. Farrell, Joshua King, Stephen Howell, Melinda A. Webster, John Paden, Carl Leuschen, Joseph A. MacGregor, Jacqueline Richter-Menge, Jeremy Harbeck, and Mark Tschudi
The Cryosphere, 11, 2571–2593, https://doi.org/10.5194/tc-11-2571-2017, https://doi.org/10.5194/tc-11-2571-2017, 2017
Short summary
Short summary
Since 2009, the ultra-wideband snow radar on Operation IceBridge has acquired data in annual campaigns conducted during the Arctic and Antarctic springs. Existing snow depth retrieval algorithms differ in the way the air–snow and snow–ice interfaces are detected and localized in the radar returns and in how the system limitations are addressed. Here, we assess five retrieval algorithms by comparisons with field measurements, ground-based campaigns, and analyzed fields of snow depth.
Alek A. Petty, Michel C. Tsamados, Nathan T. Kurtz, Sinead L. Farrell, Thomas Newman, Jeremy P. Harbeck, Daniel L. Feltham, and Jackie A. Richter-Menge
The Cryosphere, 10, 1161–1179, https://doi.org/10.5194/tc-10-1161-2016, https://doi.org/10.5194/tc-10-1161-2016, 2016
Short summary
Short summary
This study presents an analysis of Arctic sea ice topography using high-resolution, three-dimensional surface elevation data from the Airborne Topographic Mapper (ATM) laser altimeter, flown as part of NASA's Operation IceBridge mission. We describe and implement a newly developed sea ice surface feature-picking algorithm and derive novel information regarding the height, volume and geometry of surface features over the western Arctic sea ice cover.
N. T. Kurtz, N. Galin, and M. Studinger
The Cryosphere, 8, 1217–1237, https://doi.org/10.5194/tc-8-1217-2014, https://doi.org/10.5194/tc-8-1217-2014, 2014
N. T. Kurtz, S. L. Farrell, M. Studinger, N. Galin, J. P. Harbeck, R. Lindsay, V. D. Onana, B. Panzer, and J. G. Sonntag
The Cryosphere, 7, 1035–1056, https://doi.org/10.5194/tc-7-1035-2013, https://doi.org/10.5194/tc-7-1035-2013, 2013
Related subject area
Discipline: Sea ice | Subject: Antarctic
The role of atmospheric conditions in the Antarctic sea ice extent summer minima
Sources of low-frequency variability in observed Antarctic sea ice
Quantifying the Influence of Snow over Sea Ice Morphology on L-Band Microwave Satellite Observations in the Southern Ocean
A contrast in sea ice drift and deformation between winter and spring of 2019 in the Antarctic marginal ice zone
Multidecadal variability and predictability of Antarctic sea ice in the GFDL SPEAR_LO model
Signature of the stratosphere–troposphere coupling on recent record-breaking Antarctic sea-ice anomalies
Southern Ocean polynyas and dense water formation in a high-resolution, coupled Earth system model
Annual evolution of the ice–ocean interaction beneath landfast ice in Prydz Bay, East Antarctica
The response of sea ice and high-salinity shelf water in the Ross Ice Shelf Polynya to cyclonic atmosphere circulations
Antarctic sea ice regime shift associated with decreasing zonal symmetry in the Southern Annular Mode
Evolution of the dynamics, area, and ice production of the Amundsen Sea Polynya, Antarctica, 2016–2021
Modulation of the seasonal cycle of the Antarctic sea ice extent by sea ice processes and feedbacks with the ocean and the atmosphere
Ice Sheet and Sea Ice Ultrawideband Microwave radiometric Airborne eXperiment (ISSIUMAX) in Antarctica: first results from Terra Nova Bay
Influence of fast ice on future ice shelf melting in the Totten Glacier area, East Antarctica
A comparison between Envisat and ICESat sea ice thickness in the Southern Ocean
An indicator of sea ice variability for the Antarctic marginal ice zone
Physical and mechanical properties of winter first-year ice in the Antarctic marginal ice zone along the Good Hope Line
Altimetric observation of wave attenuation through the Antarctic marginal ice zone using ICESat-2
Flexural and compressive strength of the landfast sea ice in the Prydz Bay, East Antarctic
The sensitivity of landfast sea ice to atmospheric forcing in single-column model simulations: a case study at Zhongshan Station, Antarctica
An evaluation of Antarctic sea-ice thickness from the Global Ice-Ocean Modeling and Assimilation System based on in situ and satellite observations
Rectification and validation of a daily satellite-derived Antarctic sea ice velocity product
Weddell Sea polynya analysis using SMOS–SMAP apparent sea ice thickness retrieval
Eighteen-year record of circum-Antarctic landfast-sea-ice distribution allows detailed baseline characterisation and reveals trends and variability
Brief communication: The anomalous winter 2019 sea-ice conditions in McMurdo Sound, Antarctica
Southern Ocean polynyas in CMIP6 models
Airborne mapping of the sub-ice platelet layer under fast ice in McMurdo Sound, Antarctica
Evaluation of sea-ice thickness from four reanalyses in the Antarctic Weddell Sea
The Antarctic sea ice cover from ICESat-2 and CryoSat-2: freeboard, snow depth, and ice thickness
Seasonal and interannual variability of landfast sea ice in Atka Bay, Weddell Sea, Antarctica
Influence of sea-ice anomalies on Antarctic precipitation using source attribution in the Community Earth System Model
Retrieval of snow freeboard of Antarctic sea ice using waveform fitting of CryoSat-2 returns
Three years of sea ice freeboard, snow depth, and ice thickness of the Weddell Sea from Operation IceBridge and CryoSat-2
Bianca Mezzina, Hugues Goosse, François Klein, Antoine Barthélemy, and François Massonnet
The Cryosphere, 18, 3825–3839, https://doi.org/10.5194/tc-18-3825-2024, https://doi.org/10.5194/tc-18-3825-2024, 2024
Short summary
Short summary
We analyze years with extraordinarily low sea ice extent in Antarctica during summer, until the striking record in 2022. We highlight common aspects among these events, such as the fact that the exceptional melting usually occurs in two key regions and that it is related to winds with a similar direction. We also investigate whether the summer conditions are preceded by an unusual state of the sea ice during the previous winter, as well as the physical processes involved.
David B. Bonan, Jakob Dörr, Robert C. J. Wills, Andrew F. Thompson, and Marius Årthun
The Cryosphere, 18, 2141–2159, https://doi.org/10.5194/tc-18-2141-2024, https://doi.org/10.5194/tc-18-2141-2024, 2024
Short summary
Short summary
Antarctic sea ice has exhibited variability over satellite records, including a period of gradual expansion and a period of sudden decline. We use a novel statistical method to identify sources of variability in observed Antarctic sea ice changes. We find that the gradual increase in sea ice is likely related to large-scale temperature trends, and periods of abrupt sea ice decline are related to specific flavors of equatorial tropical variability known as the El Niño–Southern Oscillation.
Lu Zhou, Julienne Stroeve, Vishnu Nandan, Rosemary Willatt, Shiming Xu, Weixin Zhu, Sahra Kacimi, Stefanie Arndt, and Zifan Yang
EGUsphere, https://doi.org/10.5194/egusphere-2024-81, https://doi.org/10.5194/egusphere-2024-81, 2024
Short summary
Short summary
Snow over Antarctic sea ice, influenced by highly variable meteorological conditions and heavy snowfall, has complex stratigraphy and profound impact over the microwave signature. We employ advanced radiation transfer models to analyze the effects of complex snow properties on brightness temperatures over the sea ice in Southern Oceans. Great potential lies in the understanding of snow processes and the application to satellite retrievals.
Ashleigh Womack, Alberto Alberello, Marc de Vos, Alessandro Toffoli, Robyn Verrinder, and Marcello Vichi
The Cryosphere, 18, 205–229, https://doi.org/10.5194/tc-18-205-2024, https://doi.org/10.5194/tc-18-205-2024, 2024
Short summary
Short summary
Synoptic events have a significant influence on the evolution of Antarctic sea ice. Our current understanding of the interactions between cyclones and sea ice remains limited. Using two ensembles of buoys, deployed in the north-eastern Weddell Sea region during winter and spring of 2019, we show how the evolution and spatial pattern of sea ice drift and deformation in the Antarctic marginal ice zone were affected by the balance between atmospheric and oceanic forcing and the local ice.
Yushi Morioka, Liping Zhang, Thomas L. Delworth, Xiaosong Yang, Fanrong Zeng, Masami Nonaka, and Swadhin K. Behera
The Cryosphere, 17, 5219–5240, https://doi.org/10.5194/tc-17-5219-2023, https://doi.org/10.5194/tc-17-5219-2023, 2023
Short summary
Short summary
Antarctic sea ice extent shows multidecadal variations with its decrease in the 1980s and increase after the 2000s until 2015. Here we show that our climate model can predict the sea ice decrease by deep convection in the Southern Ocean and the sea ice increase by the surface wind variability. These results suggest that accurate simulation and prediction of subsurface ocean and atmosphere conditions are important for those of Antarctic sea ice variability on a multidecadal timescale.
Raúl R. Cordero, Sarah Feron, Alessandro Damiani, Pedro J. Llanillo, Jorge Carrasco, Alia L. Khan, Richard Bintanja, Zutao Ouyang, and Gino Casassa
The Cryosphere, 17, 4995–5006, https://doi.org/10.5194/tc-17-4995-2023, https://doi.org/10.5194/tc-17-4995-2023, 2023
Short summary
Short summary
We investigate the response of Antarctic sea ice to year-to-year changes in the tropospheric–stratospheric dynamics. Our findings suggest that, by affecting the tropospheric westerlies, the strength of the stratospheric polar vortex has played a major role in recent record-breaking anomalies in Antarctic sea ice.
Hyein Jeong, Adrian K. Turner, Andrew F. Roberts, Milena Veneziani, Stephen F. Price, Xylar S. Asay-Davis, Luke P. Van Roekel, Wuyin Lin, Peter M. Caldwell, Hyo-Seok Park, Jonathan D. Wolfe, and Azamat Mametjanov
The Cryosphere, 17, 2681–2700, https://doi.org/10.5194/tc-17-2681-2023, https://doi.org/10.5194/tc-17-2681-2023, 2023
Short summary
Short summary
We find that E3SM-HR reproduces the main features of the Antarctic coastal polynyas. Despite the high amount of coastal sea ice production, the densest water masses are formed in the open ocean. Biases related to the lack of dense water formation are associated with overly strong atmospheric polar easterlies. Our results indicate that the large-scale polar atmospheric circulation must be accurately simulated in models to properly reproduce Antarctic dense water formation.
Haihan Hu, Jiechen Zhao, Petra Heil, Zhiliang Qin, Jingkai Ma, Fengming Hui, and Xiao Cheng
The Cryosphere, 17, 2231–2244, https://doi.org/10.5194/tc-17-2231-2023, https://doi.org/10.5194/tc-17-2231-2023, 2023
Short summary
Short summary
The oceanic characteristics beneath sea ice significantly affect ice growth and melting. The high-frequency and long-term observations of oceanic variables allow us to deeply investigate their diurnal and seasonal variation and evaluate their influences on sea ice evolution. The large-scale sea ice distribution and ocean circulation contributed to the seasonal variation of ocean variables, revealing the important relationship between large-scale and local phenomena.
Xiaoqiao Wang, Zhaoru Zhang, Michael S. Dinniman, Petteri Uotila, Xichen Li, and Meng Zhou
The Cryosphere, 17, 1107–1126, https://doi.org/10.5194/tc-17-1107-2023, https://doi.org/10.5194/tc-17-1107-2023, 2023
Short summary
Short summary
The bottom water of the global ocean originates from high-salinity water formed in polynyas in the Southern Ocean where sea ice coverage is low. This study reveals the impacts of cyclones on sea ice and water mass formation in the Ross Ice Shelf Polynya using numerical simulations. Sea ice production is rapidly increased caused by enhancement in offshore wind, promoting high-salinity water formation in the polynya. Cyclones also modulate the transport of this water mass by wind-driven currents.
Serena Schroeter, Terence J. O'Kane, and Paul A. Sandery
The Cryosphere, 17, 701–717, https://doi.org/10.5194/tc-17-701-2023, https://doi.org/10.5194/tc-17-701-2023, 2023
Short summary
Short summary
Antarctic sea ice has increased over much of the satellite record, but we show that the early, strongly opposing regional trends diminish and reverse over time, leading to overall negative trends in recent decades. The dominant pattern of atmospheric flow has changed from strongly east–west to more wave-like with enhanced north–south winds. Sea surface temperatures have also changed from circumpolar cooling to regional warming, suggesting recent record low sea ice will not rapidly recover.
Grant J. Macdonald, Stephen F. Ackley, Alberto M. Mestas-Nuñez, and Adrià Blanco-Cabanillas
The Cryosphere, 17, 457–476, https://doi.org/10.5194/tc-17-457-2023, https://doi.org/10.5194/tc-17-457-2023, 2023
Short summary
Short summary
Polynyas are key sites of sea ice production, biological activity, and carbon sequestration. The Amundsen Sea Polynya is of particular interest due to its size and location. By analyzing radar imagery and climate and sea ice data products, we evaluate variations in the dynamics, area, and ice production of the Amundsen Sea Polynya. In particular, we find the local seafloor topography and associated grounded icebergs play an important role in the polynya dynamics, influencing ice production.
Hugues Goosse, Sofia Allende Contador, Cecilia M. Bitz, Edward Blanchard-Wrigglesworth, Clare Eayrs, Thierry Fichefet, Kenza Himmich, Pierre-Vincent Huot, François Klein, Sylvain Marchi, François Massonnet, Bianca Mezzina, Charles Pelletier, Lettie Roach, Martin Vancoppenolle, and Nicole P. M. van Lipzig
The Cryosphere, 17, 407–425, https://doi.org/10.5194/tc-17-407-2023, https://doi.org/10.5194/tc-17-407-2023, 2023
Short summary
Short summary
Using idealized sensitivity experiments with a regional atmosphere–ocean–sea ice model, we show that sea ice advance is constrained by initial conditions in March and the retreat season is influenced by the magnitude of several physical processes, in particular by the ice–albedo feedback and ice transport. Atmospheric feedbacks amplify the response of the winter ice extent to perturbations, while some negative feedbacks related to heat conduction fluxes act on the ice volume.
Marco Brogioni, Mark J. Andrews, Stefano Urbini, Kenneth C. Jezek, Joel T. Johnson, Marion Leduc-Leballeur, Giovanni Macelloni, Stephen F. Ackley, Alexandra Bringer, Ludovic Brucker, Oguz Demir, Giacomo Fontanelli, Caglar Yardim, Lars Kaleschke, Francesco Montomoli, Leung Tsang, Silvia Becagli, and Massimo Frezzotti
The Cryosphere, 17, 255–278, https://doi.org/10.5194/tc-17-255-2023, https://doi.org/10.5194/tc-17-255-2023, 2023
Short summary
Short summary
In 2018 the first Antarctic campaign of UWBRAD was carried out. UWBRAD is a new radiometer able to collect microwave spectral signatures over 0.5–2 GHz, thus outperforming existing similar sensors. It allows us to probe thicker sea ice and ice sheet down to the bedrock. In this work we tried to assess the UWBRAD potentials for sea ice, glaciers, ice shelves and buried lakes. We also highlighted the wider range of information the spectral signature can provide to glaciological studies.
Guillian Van Achter, Thierry Fichefet, Hugues Goosse, and Eduardo Moreno-Chamarro
The Cryosphere, 16, 4745–4761, https://doi.org/10.5194/tc-16-4745-2022, https://doi.org/10.5194/tc-16-4745-2022, 2022
Short summary
Short summary
We investigate the changes in ocean–ice interactions in the Totten Glacier area between the last decades (1995–2014) and the end of the 21st century (2081–2100) under warmer climate conditions. By the end of the 21st century, the sea ice is strongly reduced, and the ocean circulation close to the coast is accelerated. Our research highlights the importance of including representations of fast ice to simulate realistic ice shelf melt rate increase in East Antarctica under warming conditions.
Jinfei Wang, Chao Min, Robert Ricker, Qian Shi, Bo Han, Stefan Hendricks, Renhao Wu, and Qinghua Yang
The Cryosphere, 16, 4473–4490, https://doi.org/10.5194/tc-16-4473-2022, https://doi.org/10.5194/tc-16-4473-2022, 2022
Short summary
Short summary
The differences between Envisat and ICESat sea ice thickness (SIT) reveal significant temporal and spatial variations. Our findings suggest that both overestimation of Envisat sea ice freeboard, potentially caused by radar backscatter originating from inside the snow layer, and the AMSR-E snow depth biases and sea ice density uncertainties can possibly account for the differences between Envisat and ICESat SIT.
Marcello Vichi
The Cryosphere, 16, 4087–4106, https://doi.org/10.5194/tc-16-4087-2022, https://doi.org/10.5194/tc-16-4087-2022, 2022
Short summary
Short summary
The marginal ice zone (MIZ) in the Antarctic is the largest in the world ocean. Antarctic sea ice has large year-to-year changes, and the MIZ represents its most variable component. Processes typical of the MIZ have also been observed in fully ice-covered ocean and are not captured by existing diagnostics. A new statistical method has been shown to address previous limitations in assessing the seasonal cycle of MIZ extent and to provide a probability map of sea ice state in the Southern Ocean.
Sebastian Skatulla, Riesna R. Audh, Andrea Cook, Ehlke Hepworth, Siobhan Johnson, Doru C. Lupascu, Keith MacHutchon, Rutger Marquart, Tommy Mielke, Emmanuel Omatuku, Felix Paul, Tokoloho Rampai, Jörg Schröder, Carina Schwarz, and Marcello Vichi
The Cryosphere, 16, 2899–2925, https://doi.org/10.5194/tc-16-2899-2022, https://doi.org/10.5194/tc-16-2899-2022, 2022
Short summary
Short summary
First-year sea ice has been sampled at the advancing outer edge of the Antarctic marginal ice zone (MIZ) along the Good Hope Line. Ice cores were extracted from five pancake ice floes and subsequently analysed for their physical and mechanical properties. Of particular interest was elucidating the transition of ice composition within the MIZ in terms of differences in mechanical stiffness and strength properties as linked to physical and textural characteristics at early-stage ice formation.
Jill Brouwer, Alexander D. Fraser, Damian J. Murphy, Pat Wongpan, Alberto Alberello, Alison Kohout, Christopher Horvat, Simon Wotherspoon, Robert A. Massom, Jessica Cartwright, and Guy D. Williams
The Cryosphere, 16, 2325–2353, https://doi.org/10.5194/tc-16-2325-2022, https://doi.org/10.5194/tc-16-2325-2022, 2022
Short summary
Short summary
The marginal ice zone is the region where ocean waves interact with sea ice. Although this important region influences many sea ice, ocean and biological processes, it has been difficult to accurately measure on a large scale from satellite instruments. We present new techniques for measuring wave attenuation using the NASA ICESat-2 laser altimeter. By measuring how waves attenuate within the sea ice, we show that the marginal ice zone may be far wider than previously realised.
Qingkai Wang, Zhaoquan Li, Peng Lu, Yigang Xu, and Zhijun Li
The Cryosphere, 16, 1941–1961, https://doi.org/10.5194/tc-16-1941-2022, https://doi.org/10.5194/tc-16-1941-2022, 2022
Short summary
Short summary
A large area of landfast sea ice exists in the Prydz Bay, and it is always a safety concern to transport cargos on ice to the research stations. Knowing the mechanical properties of sea ice is helpful to solve the issue; however, these data are rarely reported in this region. We explore the effects of sea ice physical properties on the flexural strength, effective elastic modulus, and uniaxial compressive strength, which gives new insights into assessing the bearing capacity of landfast sea ice.
Fengguan Gu, Qinghua Yang, Frank Kauker, Changwei Liu, Guanghua Hao, Chao-Yuan Yang, Jiping Liu, Petra Heil, Xuewei Li, and Bo Han
The Cryosphere, 16, 1873–1887, https://doi.org/10.5194/tc-16-1873-2022, https://doi.org/10.5194/tc-16-1873-2022, 2022
Short summary
Short summary
The sea ice thickness was simulated by a single-column model and compared with in situ observations obtained off Zhongshan Station in the Antarctic. It is shown that the unrealistic precipitation in the atmospheric forcing data leads to the largest bias in sea ice thickness and snow depth modeling. In addition, the increasing snow depth gradually inhibits the growth of sea ice associated with thermal blanketing by the snow.
Sutao Liao, Hao Luo, Jinfei Wang, Qian Shi, Jinlun Zhang, and Qinghua Yang
The Cryosphere, 16, 1807–1819, https://doi.org/10.5194/tc-16-1807-2022, https://doi.org/10.5194/tc-16-1807-2022, 2022
Short summary
Short summary
The Global Ice-Ocean Modeling and Assimilation System (GIOMAS) can basically reproduce the observed variability in Antarctic sea-ice volume and its changes in the trend before and after 2013, and it underestimates Antarctic sea-ice thickness (SIT) especially in deformed ice zones. Assimilating additional sea-ice observations with advanced assimilation methods may result in a more accurate estimation of Antarctic SIT.
Tian R. Tian, Alexander D. Fraser, Noriaki Kimura, Chen Zhao, and Petra Heil
The Cryosphere, 16, 1299–1314, https://doi.org/10.5194/tc-16-1299-2022, https://doi.org/10.5194/tc-16-1299-2022, 2022
Short summary
Short summary
This study presents a comprehensive validation of a satellite observational sea ice motion product in Antarctica by using drifting buoys. Two problems existing in this sea ice motion product have been noticed. After rectifying problems, we use it to investigate the impacts of satellite observational configuration and timescale on Antarctic sea ice kinematics and suggest the future improvement of satellite missions specifically designed for retrieval of sea ice motion.
Alexander Mchedlishvili, Gunnar Spreen, Christian Melsheimer, and Marcus Huntemann
The Cryosphere, 16, 471–487, https://doi.org/10.5194/tc-16-471-2022, https://doi.org/10.5194/tc-16-471-2022, 2022
Short summary
Short summary
In this paper we show that the activity leading to the open-ocean polynyas near the Maud Rise seamount that have occurred repeatedly from 1974–1976 as well as 2016–2017 does not simply stop for polynya-free years. Using apparent sea ice thickness retrieval, we have identified anomalies where there is thinning of sea ice on a scale that is comparable to that of the polynya events of 2016–2017. These anomalies took place in 2010, 2013, 2014 and 2018.
Alexander D. Fraser, Robert A. Massom, Mark S. Handcock, Phillip Reid, Kay I. Ohshima, Marilyn N. Raphael, Jessica Cartwright, Andrew R. Klekociuk, Zhaohui Wang, and Richard Porter-Smith
The Cryosphere, 15, 5061–5077, https://doi.org/10.5194/tc-15-5061-2021, https://doi.org/10.5194/tc-15-5061-2021, 2021
Short summary
Short summary
Landfast ice is sea ice that remains stationary by attaching to Antarctica's coastline and grounded icebergs. Although a variable feature, landfast ice exerts influence on key coastal processes involving pack ice, the ice sheet, ocean, and atmosphere and is of ecological importance. We present a first analysis of change in landfast ice over an 18-year period and quantify trends (−0.19 ± 0.18 % yr−1). This analysis forms a reference of landfast-ice extent and variability for use in other studies.
Greg H. Leonard, Kate E. Turner, Maren E. Richter, Maddy S. Whittaker, and Inga J. Smith
The Cryosphere, 15, 4999–5006, https://doi.org/10.5194/tc-15-4999-2021, https://doi.org/10.5194/tc-15-4999-2021, 2021
Short summary
Short summary
McMurdo Sound sea ice can generally be partitioned into two regimes: a stable fast-ice cover forming south of approximately 77.6° S and a more dynamic region north of 77.6° S that is regularly impacted by polynyas. In 2019, a stable fast-ice cover formed unusually late due to repeated break-out events. This subsequently affected sea-ice operations in the 2019/20 field season. We analysed the 2019 sea-ice conditions and found a strong correlation with unusually large southerly wind events.
Martin Mohrmann, Céline Heuzé, and Sebastiaan Swart
The Cryosphere, 15, 4281–4313, https://doi.org/10.5194/tc-15-4281-2021, https://doi.org/10.5194/tc-15-4281-2021, 2021
Short summary
Short summary
Polynyas are large open-water areas within the sea ice. We developed a method to estimate their area, distribution and frequency for the Southern Ocean in climate models and observations. All models have polynyas along the coast but few do so in the open ocean, in contrast to observations. We examine potential atmospheric and oceanic drivers of open-water polynyas and discuss recently implemented schemes that may have improved some models' polynya representation.
Christian Haas, Patricia J. Langhorne, Wolfgang Rack, Greg H. Leonard, Gemma M. Brett, Daniel Price, Justin F. Beckers, and Alex J. Gough
The Cryosphere, 15, 247–264, https://doi.org/10.5194/tc-15-247-2021, https://doi.org/10.5194/tc-15-247-2021, 2021
Short summary
Short summary
We developed a method to remotely detect proxy signals of Antarctic ice shelf melt under adjacent sea ice. It is based on aircraft surveys with electromagnetic induction sounding. We found year-to-year variability of the ice shelf melt proxy in McMurdo Sound and spatial fine structure that support assumptions about the melt of the McMurdo Ice Shelf. With this method it will be possible to map and detect locations of intense ice shelf melt along the coast of Antarctica.
Qian Shi, Qinghua Yang, Longjiang Mu, Jinfei Wang, François Massonnet, and Matthew R. Mazloff
The Cryosphere, 15, 31–47, https://doi.org/10.5194/tc-15-31-2021, https://doi.org/10.5194/tc-15-31-2021, 2021
Short summary
Short summary
The ice thickness from four state-of-the-art reanalyses (GECCO2, SOSE, NEMO-EnKF and GIOMAS) are evaluated against that from remote sensing and in situ observations in the Weddell Sea, Antarctica. Most of the reanalyses can reproduce ice thickness in the central and eastern Weddell Sea but failed to capture the thick and deformed ice in the western Weddell Sea. These results demonstrate the possibilities and limitations of using current sea-ice reanalysis in Antarctic climate research.
Sahra Kacimi and Ron Kwok
The Cryosphere, 14, 4453–4474, https://doi.org/10.5194/tc-14-4453-2020, https://doi.org/10.5194/tc-14-4453-2020, 2020
Short summary
Short summary
Our current understanding of Antarctic ice cover is largely informed by ice extent measurements from passive microwave sensors. These records, while useful, provide a limited picture of how the ice is responding to climate change. In this paper, we combine measurements from ICESat-2 and CryoSat-2 missions to assess snow depth and ice thickness of the Antarctic ice cover over an 8-month period (April through November 2019). The potential impact of salinity in the snow layer is discussed.
Stefanie Arndt, Mario Hoppmann, Holger Schmithüsen, Alexander D. Fraser, and Marcel Nicolaus
The Cryosphere, 14, 2775–2793, https://doi.org/10.5194/tc-14-2775-2020, https://doi.org/10.5194/tc-14-2775-2020, 2020
Hailong Wang, Jeremy G. Fyke, Jan T. M. Lenaerts, Jesse M. Nusbaumer, Hansi Singh, David Noone, Philip J. Rasch, and Rudong Zhang
The Cryosphere, 14, 429–444, https://doi.org/10.5194/tc-14-429-2020, https://doi.org/10.5194/tc-14-429-2020, 2020
Short summary
Short summary
Using a climate model with unique water source tagging, we found that sea-ice anomalies in the Southern Ocean and accompanying SST changes have a significant influence on Antarctic precipitation and its source attribution through their direct impact on moisture sources and indirect impact on moisture transport. This study also highlights the importance of atmospheric dynamics in affecting the thermodynamic impact of sea-ice anomalies on regional Antarctic precipitation.
Steven W. Fons and Nathan T. Kurtz
The Cryosphere, 13, 861–878, https://doi.org/10.5194/tc-13-861-2019, https://doi.org/10.5194/tc-13-861-2019, 2019
Short summary
Short summary
A method to measure the snow freeboard of Antarctic sea ice from CryoSat-2 data is developed. Through comparisons with data from airborne campaigns and another satellite mission, we find that this method can reasonably retrieve snow freeboard across the Antarctic and shows promise in retrieving snow depth in certain locations. Snow freeboard data from CryoSat-2 are important because they enable the calculation of sea ice thickness and help to better understand snow depth on Antarctic sea ice.
Ron Kwok and Sahra Kacimi
The Cryosphere, 12, 2789–2801, https://doi.org/10.5194/tc-12-2789-2018, https://doi.org/10.5194/tc-12-2789-2018, 2018
Short summary
Short summary
The variability of snow depth and ice thickness in three years of repeat surveys of an IceBridge (OIB) transect across the Weddell Sea is examined. Retrieved thicknesses suggest a highly variable but broadly thicker ice cover compared to that inferred from drilling and ship-based measurements. The use of lidar and radar altimeters to estimate snow depth for thickness calculations is analyzed, and the need for better characterization of biases due to radar penetration effects is highlighted.
Cited articles
Arthern, R. J., Wingham, D. J., and Ridout, A. L.: Controls on ERS altimeter
measurements over ice sheets: Footprint-scale topography, backscatter
fluctuations, and the dependence of microwave penetration depth on satellite
orientation, J. Geophys. Res.-Atmos., 106,
33471–33484, https://doi.org/10.1029/2001JD000498, 2001. a
Beaven, S. G., Lockhart, G. L., Gogineni, S. P., Hossetnmostafa, A. R., Jezek,
K., Gow, A. J., Perovich, D. K., Fung, A. K., and Tjuatja, S.: Laboratory
measurements of radar backscatter from bare and snow-covered saline ice
sheets, Int. J. Remote Sens., 16, 851–876,
https://doi.org/10.1080/01431169508954448, 1995. a, b
Brown, G. S.: The average impulse response of a rough surface and Its
applications, IEEE J. Oceanic Eng., 2, 67–74,
https://doi.org/10.1109/JOE.1977.1145328, 1977. a
Comiso, J. C.: Bootstrap sea ice concentrations from Nimbus-7 SMMR and DMSP
SSM/I-SSMIS, version 3, NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/7Q8HCCWS4I0R, 2017. a
EPA: Climate change indicators in the United States, Tech. Rep. April,
http://www.epa.gov/climatechange/ (last access: 6 April 2021), 2016. a
European Space Agency: L1b SAR precise orbit. Baseline D, Earth Online [data set],
https://doi.org/10.5270/CR2-2cnblvi, 2019a. a, b
European Space Agency: L1b SARIn precise orbit. Baseline D, Earth Online [data set],
https://doi.org/10.5270/CR2-u3805kw, 2019b. a
European Space Agency: CryoSat-2 product handbook: Baseline D 1.1, Tech.
rep.,
https://earth.esa.int/documents/10174/125272/CryoSat-Baseline-D-Product-Handbook (last access: 10 October 2022),
2019c. a
Farrell, S. L., Laxon, S. W., McAdoo, D. C., Yi, D., and Zwally, H. J.: Five
years of Arctic sea ice freeboard measurements from the Ice, Cloud and land
Elevation Satellite, J. Geophys. Res., 114, C04008,
https://doi.org/10.1029/2008JC005074, 2009. a
Fons, S., Kurtz, N., and Bagnardi, M.: Antarctic Sea Ice Thickness Estimates from CryoSat-2: 2010–2021 (0.1.1), Zenodo [data set] https://doi.org/10.5281/zenodo.7327711, 2022.
Garnier, F., Bocquet, M., Fleury, S., Bouffard, J., Tsamados, M., Remy, F.,
Garric, G., and Chenal, A.: Latest Altimetry-Based Sea Ice Freeboard and
Volume Inter-Annual Variability in the Antarctic over 2003–2020, Remote
Sens., 14, 4741, https://doi.org/10.3390/rs14194741, 2022.
a, b, c, d
Giles, K. A., Laxon, S. W., and Worby, A. P.: Antarctic sea ice elevation from
satellite radar altimetry, Geophys. Res. Lett., 35, 1–5,
https://doi.org/10.1029/2007GL031572, 2008. a
Giovinetto, M. B., Bromwich, D. H., and Wendler, G.: Atmospheric net transport
of water vapor and latent heat across 70∘ S, J. Geophys. Res., 97, 917–930, https://doi.org/10.1029/91JD02485, 1992. a
Hendricks, S., Paul, S., and Rinne, E.: ESA Sea Ice Climate Change Initiative
(Sea_Ice_cci): Southern hemisphere sea ice thickness from CryoSat-2 on
the satellite swath (L2P), v2.0, Centre for Environmental Data Analysis [data set],
https://doi.org/10.5285/fbfae06e787b4fefb4b03cba2fd04bc3, 2018. a, b, c
Herdman, H. F. P.: Early Discoverers XII: Some Notes on Sea Ice Observed By
Captain James Cook, R.N., During his Circumnavigation of Antarctica,
1772–75, J. Glaciol., 3, 534–541,
https://doi.org/10.3189/S0022143000017287, 1959. a
Holland, P. R.: The seasonality of Antarctic sea ice trends, Geophys.
Res. Lett., 41, 4230–4237, https://doi.org/10.1002/2014GL060172, 2014. a
Hutchings, J. K., Heil, P., Lecomte, O., Stevens, R., Steer, A., and Lieser,
J. L.: Comparing methods of measuring sea-ice density in the East Antarctic,
Ann. Glaciol., 56, 77–82, https://doi.org/10.3189/2015AoG69A814, 2015. a
Intergovernmental Panel on Climate Change (IPCC): Polar Regions, in: The Oceaon and Cryosphere in a Changing Climate, Cambridge University Press,
203–320, https://doi.org/10.1017/9781009157964.005, 2022. a
Kern, S. and Ozsoy-Çiçek, B.: Satellite remote sensing of snow
depth on Antarctic sea ice: an inter-comparison of two empirical approaches,
Remote Sens., 8, 450, https://doi.org/10.3390/rs8060450, 2016. a, b, c
Kern, S. and Spreen, G.: Uncertainties in Antarctic sea-ice thickness
retrieval from ICESat, Ann. Glaciol., 56, 107–119,
https://doi.org/10.3189/2015AoG69A736, 2015. a
Kurtz, N., Studinger, M., Harbeck, J., Onana, V., and Yi, D.: IceBridge L4 sea
ice freeboard, snow depth, and thickness, version 1, National Snow and Ice Data Center [data set],
https://doi.org/10.5067/G519SHCKWQV6, 2015. a
Kurtz, N. T. and Markus, T.: Satellite observations of Antarctic sea ice
thickness and volume, J. Geophys. Res.-Oceans, 117, C08025,
https://doi.org/10.1029/2012JC008141, 2012 (data available at: https://earth.gsfc.nasa.gov/cryo/data/antarctic-sea-ice-thickness, last access: 14 September 2022). a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q
Kurtz, N. T., Markus, T., Cavalieri, D. J., Krabill, W., Sonntag, J. G., and
Miller, J.: Comparison of ICESat data with airborne laser altimeter
measurements over arctic sea ice, IEEE T. Geosci. Remote, 46, 1913–1924, https://doi.org/10.1109/TGRS.2008.916639, 2008. a
Kwok, R.: Satellite remote sensing of sea-ice thickness and kinematics: A
review, J. Glaciol., 56, 1129–1140,
https://doi.org/10.3189/002214311796406167, 2011. a
Kwok, R.: Simulated effects of a snow layer on retrieval of CryoSat-2 sea ice
freeboard, Geophys. Res. Lett., 41, 5014–5020,
https://doi.org/10.1002/2014GL060993, 2014. a, b
Kwok, R. and Cunningham, G. F.: Variability of arctic sea ice thickness and
volume from CryoSat-2, Philos. T. R. Soc. A, 373, 20140157,
https://doi.org/10.1098/rsta.2014.0157, 2015. a
Kwok, R. and Kacimi, S.: Three years of sea ice freeboard, snow depth, and ice thickness of the Weddell Sea from Operation IceBridge and CryoSat-2, The Cryosphere, 12, 2789–2801, https://doi.org/10.5194/tc-12-2789-2018, 2018. a
Kwok, R. and Maksym, T.: Snow depth of the Weddell and Bellingshausen sea ice
covers from IceBridge surveys in 2010 and 2011: An examination, J. Geophys. Res.-Oceans, 119, 4141–4167, https://doi.org/10.1002/2014JC009943,
2014. a
Kwok, R., Cunningham, G. F., Zwally, H. J., and Yi, D.: Ice, Cloud, and land
Elevation Satellite (ICESat) over Arctic sea ice: Retrieval of freeboard,
J. Geophys. Res.-Oceans, 112, C12013,
https://doi.org/10.1029/2006JC003978, 2007. a
Kwok, R., Kacimi, S., Webster, M. A., Kurtz, N. T., and Petty, A. A.: Arctic
snow depth and sea ice thickness from ICESat-2 and CryoSat-2 freeboards: a
first examination, J. Geophys. Res.-Oceans, 125,
e2019JC016008, https://doi.org/10.1029/2019JC016008, 2020. a
Kwok, R., Petty, A., Cunningham, G., Markus, T., Hancock, D., Ivanoff, A.,
Wimert, J., Bagnardi, M., and Kurtz, N.: ATLAS/ICESat-2 L3A Sea Ice
Freeboard, Version 5, National Snow and Ice Data Center [data set], https://doi.org/10.5067/ATLAS/ATL10.005, 2021. a, b
Kwok, R., Petty, A., Bagnardi, M., Wimert, J. T., Cunningham, G. F., Hancock,
D. W., Ivanoff, A., and Kurtz, N.: Icesat-2 algorithm theoretical basis
document for sea ice products (atl07/atl10) release 005 Ice, Cloud, and land
Elevation satellite (ICESat-2) project algorithm theoretical basis document
(ATBD) for sea ice products, Tech. rep.,
https://nsidc.org/sites/default/files/icesat2_atl07_atl10_atl20_atl21_atbd_r005_1.pdf (last access: 14 September 2022),
2022. a
Landy, J. C., Petty, A. A., Tsamados, M., and Stroeve, J. C.: Sea ice
roughness overlooked as a key source of uncertainty in CryoSat-2 Ice
freeboard retrievals, J. Geophys. Res.-Oceans, 125, e2019JC015820,
https://doi.org/10.1029/2019JC015820, 2020. a
Laxon, S., Peacock, H., and Smith, D.: High interannual variability of sea ice
thickness in the Arctic region, Nature, 425, 947–950,
https://doi.org/10.1038/nature02050, 2003. a
Laxon, S. W., Giles, K. A., Ridout, A. L., Wingham, D. J., Willatt, R., Cullen,
R., Kwok, R., Schweiger, A., Zhang, J., Haas, C., Hendricks, S., Krishfield,
R., Kurtz, N., Farrell, S., and Davidson, M.: CryoSat-2 estimates of Arctic
sea ice thickness and volume, Geophys. Res. Lett., 40, 732–737,
https://doi.org/10.1002/grl.50193, 2013. a, b
Li, H., Xie, H., Kern, S., Wan, W., Ozsoy, B., Ackley, S., and Hong, Y.:
Spatio-temporal variability of Antarctic sea-ice thickness and volume
obtained from ICESat data using an innovative algorithm, Remote Sens.
Environ., 219, 44–61, https://doi.org/10.1016/j.rse.2018.09.031, 2018. a, b, c
Liston, G. E., Polashenski, C., Rösel, A., Itkin, P., King, J.,
Merkouriadi, I., and Haapala, J.: A distributed snow-evolution model for
sea-ice applications (snowmodel), J. Geophys. Res.-Oceans,
123, 3786–3810, https://doi.org/10.1002/2017JC013706, 2018. a
Liston, G. E., Itkin, P., Stroeve, J., Tschudi, M., Stewart, J. S., Pedersen,
S. H., Reinking, A. K., and Elder, K.: A Lagrangian Snow-Evolution System for
Sea-Ice Applications (SnowModel-LG): Part I: Model Description, J. Geophys. Res.-Oceans, 125, e2019JC015913,
https://doi.org/10.1029/2019JC015913, 2020. a
Maksym, T. and Jeffries, M. O.: A one-dimensional percolation model of
flooding and snow ice formation on Antarctic sea ice, J. Geophys.
Res.-Oceans, 105, 26313–26331, https://doi.org/10.1029/2000JC900130, 2000. a
Maksym, T. and Markus, T.: Antarctic sea ice thickness and snow-to-ice
conversion from atmospheric reanalysis and passive microwave snow depth,
J. Geophys. Res.-Oceans, 113, C02S12,
https://doi.org/10.1029/2006JC004085, 2008. a, b, c
Mallett, R. D. C., Lawrence, I. R., Stroeve, J. C., Landy, J. C., and Tsamados, M.: Brief communication: Conventional assumptions involving the speed of radar waves in snow introduce systematic underestimates to sea ice thickness and seasonal growth rate estimates, The Cryosphere, 14, 251–260, https://doi.org/10.5194/tc-14-251-2020, 2020. a
Markus, T. and Cavalieri, D. J.: Snow depth distribution over sea ice in the
southern ocean from satellite passive microwave data, in: Antarctic Sea Ice:
Physical Processes, Interactions and Variability, edited by: Jeffries, M.,
American Geophysical Union, 19–39 pp., https://doi.org/10.1029/AR074p0019,
1998. a, b, c
Massom, R. A., Eicken, H., Haas, C., Jeffries, M. O., Drinkwater, M. R., Sturm,
M., Worby, A. P., Wu, X., Lytle, V. I., Ushio, S., Morris, K., Reid, P. A.,
Warren, S. G., and Allison, I.: Snow on Antarctic sea ice, Rev.
Geophys., 39, 413–445, https://doi.org/10.1029/2000RG000085, 2001. a, b
Meredith, M., Sommerkorn, M., Cassota, S., Derksen, C., Ekaykin, A., Hollowed,
A., Kofinas, G., Mackintosh, A., Melbourne-Thomas, J., Muelbert, M.,
Ottersen, G., Pritchard, H., Schuur, E., Boyd, P., Hobbs, W., and
Hodgson-Johnston, I.: Polar regions, IPCC Special Report on the Ocean and
Cryosphere in a Changing Climate, https://doi.org/10.1017/9781009157964.005, 2019. a
Nichols, T., Berkes, F., Jolly, D., Snow, N., and The Community of Sachs
Harbour: Climate Change and Sea Ice: Local Observations from the Canadian
Western Arctic, Arctic, 57, 68–79, https://doi.org/10.14430/arctic484, 2004. a
Ozsoy-Cicek, B., Ackley, S., Xie, H., Yi, D., and Zwally, J.: Sea ice thickness
retrieval algorithms based on in situ surface elevation and thickness values
for application to altimetry, J. Geophys. Res.-Oceans, 118,
3807–3822, https://doi.org/10.1002/jgrc.20252, 2013. a, b
Parkinson, C. L.: A 40-y record reveals gradual Antarctic sea ice increases
followed by decreases at rates far exceeding the rates seen in the Arctic,
P. Natl. Acad. Sci. USA, 116, 14414–14423, https://doi.org/10.1073/pnas.1906556116, 2019. a, b, c
Paul, S., Hendricks, S., Ricker, R., Kern, S., and Rinne, E.: Empirical parametrization of Envisat freeboard retrieval of Arctic and Antarctic sea ice based on CryoSat-2: progress in the ESA Climate Change Initiative, The Cryosphere, 12, 2437–2460, https://doi.org/10.5194/tc-12-2437-2018, 2018. a, b, c, d, e, f
Persson, O. and Vihma, T.: The atmosphere over sea ice, in: Sea Ice, 3rd edn., John Wiley & Sons, Ltd., https://doi.org/10.1002/9781118778371.ch6, 2016. a
Petty, A. A., Webster, M., Boisvert, L., and Markus, T.: The NASA Eulerian Snow on Sea Ice Model (NESOSIM) v1.0: initial model development and analysis, Geosci. Model Dev., 11, 4577–4602, https://doi.org/10.5194/gmd-11-4577-2018, 2018. a
Ricker, R., Hendricks, S., Helm, V., Skourup, H., and Davidson, M.: Sensitivity of CryoSat-2 Arctic sea-ice freeboard and thickness on radar-waveform interpretation, The Cryosphere, 8, 1607–1622, https://doi.org/10.5194/tc-8-1607-2014, 2014. a, b
Schwegmann, S., Rinne, E., Ricker, R., Hendricks, S., and Helm, V.: About the consistency between Envisat and CryoSat-2 radar freeboard retrieval over Antarctic sea ice, The Cryosphere, 10, 1415–1425, https://doi.org/10.5194/tc-10-1415-2016, 2016. a, b, c, d
Spreen, G., Kern, S., Stammer, D., and Hansen, E.: Fram Strait sea ice volume
export estimated between 2003 and 2008 from satellite data, Geophys.
Res. Lett., 36, L19502, https://doi.org/10.1029/2009GL039591, 2009. a, b
Stewart, J. S., Meier, W. N., and Scott, D. J.: Polar Stereographic Ancillary
Grid Information, Version 1, National Snow and Ice Data Center [data set], https://doi.org/10.5067/N6INPBT8Y104, 2022. a
Tilling, R., Ridout, A., and Shepherd, A.: Assessing the impact of lead and
floe sampling on Arctic sea ice thickness estimates from Envisat and
CryoSat‐2, J. Geophys. Res.-Oceans, 124, 7473–7485,
https://doi.org/10.1029/2019JC015232, 2019. a
Tilling, R. L., Ridout, A., and Shepherd, A.: Estimating Arctic sea ice
thickness and volume using CryoSat-2 radar altimeter data, Adv. Space
Res., 62, 1203–1225, https://doi.org/10.1016/j.asr.2017.10.051, 2018. a, b, c, d
Warren, S. G., Rigor, I. G., Untersteiner, N., Radionov, V. F., Bryazgin,
N. N., Aleksandrov, Y. I., and Colony, R.: Snow depth on Arctic sea ice,
J. Climate, 12, 1814–1829,
https://doi.org/10.1175/1520-0442(1999)012<1814:SDOASI>2.0.CO;2, 1999. a
Willatt, R. C., Giles, K. A., Laxon, S. W., Stone-Drake, L., and Worby, A. P.:
Field investigations of Ku-band radar penetration into snow cover on
antarctic sea ice, IEEE T. Geosci. Remote, 48,
365–372, https://doi.org/10.1109/TGRS.2009.2028237, 2010. a, b, c
Williams, G., Maksym, T., Wilkinson, J., Kunz, C., Murphy, C., Kimball, P., and
Singh, H.: Thick and deformed Antarctic sea ice mapped with autonomous
underwater vehicles, Nature Geosci., 8, 61–67, https://doi.org/10.1038/ngeo2299,
2015. a
Wingham, D. J., Francis, C. R., Baker, S., Bouzinac, C., Brockley, D., Cullen,
R., de Chateau-Thierry, P., Laxon, S. W., Mallow, U., Mavrocordatos, C.,
Phalippou, L., Ratier, G., Rey, L., Rostan, F., Viau, P., and Wallis, D. W.:
CryoSat: A mission to determine the fluctuations in Earth's land and marine
ice fields, Adv. Space Res., 37, 841–871,
https://doi.org/10.1016/j.asr.2005.07.027, 2006. a
Zwally, H. J., Schutz, B., Abdalati, W., Abshire, J., Bentley, C., Brenner, A.,
Bufton, J., Dezio, J., Hancock, D., Harding, D., Herring, T., Minster, B.,
Quinn, K., Palm, S., Spinhirne, J., and Thomas, R.: ICESat's laser
measurements of polar ice, atmosphere, ocean, and land, J.
Geodyn., 34, 405–445, https://doi.org/10.1016/S0264-3707(02)00042-X, 2002. a
Short summary
Antarctic sea ice thickness is an important quantity in the Earth system. Due to the thick and complex snow cover on Antarctic sea ice, estimating the thickness of the ice pack is difficult using traditional methods in radar altimetry. In this work, we use a waveform model to estimate the freeboard and snow depth of Antarctic sea ice from CryoSat-2 and use these values to calculate sea ice thickness and volume between 2010 and 2021 and showcase how the sea ice pack has changed over this time.
Antarctic sea ice thickness is an important quantity in the Earth system. Due to the thick and...
